Academic Activities

Editorial Boards

Data Mining and Knowledge Discovery: Action Editor, since 2018
ECML/PKDD Journal Track: Guest Editorial Board for DAMI and MACH, since 2014
Data Mining and Knowledge Discovery: Editorial Board, 2016-2017
Big Data Research: Special Issue Guest Editor (Big Data in Epidemics), 2020-2021
PVLDB: Reviewer Board, 2016

Program Committee Memberships

Area chair & Senior PC member

ECML/PKDD: European Conference on Machine Learning and Principles and Practice on Knowledge Discovery in Databases, 2020-2022 (Area Chair)
IJCAI: International Joint Conference on Artificial Intelligence, 2017-2022 (Senior PC member)
ICDM: IEEE International Conference on Data Mining, 2021 (Area Chair)
ICDE: International Conference on Data Engineering, 2020 (PC Vice-Chair)
IDA: International Symposium on Intelligent Data Analysis, 2012-2016, 2017-2020 (Senior PC member)

PC member

SDM: SIAM Conference on Data Mining, 2022
SIGKDD: ACM Conference on Knowledge Discovery and Data Mining, 2011-2012, 2018-2022
ICDM: IEEE International Conference on Data Mining, 2020, 2022
ECML/PKDD: European Conference on Machine Learning and Principles and Practice on Knowledge Discovery in Databases, 2011-2019
AAAI: AAAI Conference on Artificial Intelligence, 2017-2018
Discovery Science: International Conference on Discovery Science, 2011-2013, 2016, 2018
CIKM: ACM International Conference on Information and Knowledge Management, 2010-2015, 2018-2020
VLDB: International Conference on Very Large Data Bases, 2016-2017
SSDBM: IEEE Conference on Scientific and Statistical Database Management, 2010

Tutorials in scientific conferences

AIME 2022: Machine learning for complex medical temporal sequences
IEEE Big Data 2020: Learning from complex medical data
KDD 2019: Mining and model understanding on medical data
KDD 2018: Knowledge Discovery from Cohorts, Electronic Health Records and further Patient-related data
ICDM 2017: Mining Cohorts & Patient Data: Challenges and Solutions for the Pre-Mining, the Mining and the Post-Mining Phases
ECML/PKDD 2016: Learning from Hospital Data and Learning from Cohorts

Regular Reviewer for the following Journals

DAMI: Data Mining and Knowledge Discovery
MACH: Machine Learning
TKDE: IEEE Transactions on Knowledge and Data Engineering
TODS: ACM Transactions on Database Systems
TKDD: ACM Transactions on Knowledge Discovery and Data Mining
Neuroinformatics
KAIS: Knowledge and Information Systems

Conference/Workshop Organization

DSDAH 2018: The first International Workshop on Data Science for Digital Art History – in conjunction with the ACM International Conference on Knowledge Discovery and Data Mining
IDA 2016: The fifteenth International Symposium on Intelligent Data Analysis
COMMPER 2012: The second International Workshop on Mining Communities and People Recommenders – in conjunction with the European Conference on Machine Learning and Principles and Practice on Knowledge Discovery in Databases (ECML PKDD)
SN2AE 2012: The first International Workshop on Social and Sensor Networks in Assistive Environments – in conjunction with the ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA)
COMMPER 2011: The first International Workshop on Mining Communities and People Recommenders – in conjunction with the IEEE International Conference on Data Mining (ICDM)

Research and Teaching Assistant

Postdoctoral Researcher: Aalto University, Finland, 2009-2012
Research Assistant: Boston University, USA, 2004-2009
Teaching Assistant: Boston University, USA, 2004-2009

Software Developer

Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, Greece, 2001-2003

Paper accepted at MACH journal 2024: "Glacier: Guided Locally Constrained Counterfactual Explanations for Time Series Classification"

Paper accepted at MACH journal 2024: "iJUICE: integer JUstIfied Counterfactual Explanations"

Paper accepted at DAMI journal (ECML/PKDD journal track 2023): "Z-Time: efficient and effective interpretable multivariate time series classification"

Paper accepted at ICDM 2023: "Counterfactual Explanations for Time Series Forecasting"

Paper accepted at IDA 2023: "Explaining Black Box Reinforcement Learning Agents Through Counterfactual Policies"

Paper accepted at Discovery Science 2022: "JUICE: JUstIfied Counterfactual Explanations"

Paper accepted at ECML/PKDD 2022: "Finding local groupings of time series"

Paper accepted at ECML/PKDD 2022-DEMO track: "Demonstrator on Counterfactual Explanations for Differentially Private Support Vector Machines"

Paper accepted at CBMS 2022 for: "FLICU: A Federated Learning Workflow for Intensive Care Unit Mortality Prediction"

Paper accepted at AIME 2022 for: "EpidRLearn: Learning intervention strategies for epidemics with Reinforcement Learning"

Best paper award at AIME 2021 for: "Counterfactual Explanations for Survival Prediction of Cardiovascular ICU Patients"

Paper accepted at the DAMI journal: "SMILE: A feature-based temporal abstraction framework for event-interval sequence classification"

Paper accepted at the journal of Artificial Intelligence in Medicine: "Exploiting Complex Medical Data with Interpretable Deep Learning for Adverse Drug Event Prediction"

Paper accepted at KDD 2020: "Z-Miner: an efficient method for mining frequent arrangements of event intervals"

Paper accepted at ECML/PKDD 2020: "Z-Embedding: a spectral representation of event intervals for efficient clustering and classification"

Paper accepted at ECML/PKDD 2020: "Prediction of Global Navigation Satellite System Positioning Errors with Guarantees"

Paper accepted at CBMS 2020: "A Clustering Framework for Patient Phenotyping with Application to Adverse Drug Events"

Paper accepted at CBMS 2020: "Clinical Predictive Keyboard using Statistical and Neural Language Modeling"

Paper accepted at CBMS 2020: "Mining disproportional frequent arrangements of event intervals for investigating adverse drug events"

Paper accepted at CBMS 2020: "Evaluating Local Interpretable Model-Agnostic Explanations on Clinical Machine Learning Classification Models"

Paper accepted at KAIS: "Locally and globally explainable time series tweaking"